Abstract:The advances in the field of Automated Machine Learning (AutoML) have greatly reduced human effort in selecting and optimizing machine learning algorithms. These advances, however, have not yet widely made it to Recommender-Systems libraries. We introduce Auto-CaseRec, a Python framework based on the CaseRec recommender-system library. Auto-CaseRec provides automated algorithm selection and parameter tuning for recommendation algorithms. An initial evaluation of Auto-CaseRec against the baselines shows an avera… Show more
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